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Record W3034864865 · doi:10.2337/db20-924-p

924-P: Exploring Potential Mediators of the Cardiovascular Benefit of Dulaglutide in REWIND

2020· article· en· W3034864865 on OpenAlexaboutno aff
Helen M. Colhoun, Clinton M. Hasenour, Matthew C. Riddle, Kelley R. Branch, Маниге Кониг, Charles Atisso, Mark Lakshmanan, Reema Mody, Hertzel C. Gerstein

Bibliographic record

VenueDiabetes · 2020
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMaceMedicineHazard ratioMyocardial infarctionBlood pressureInternal medicinePopulationPlaceboCardiologyPhysical therapyPercutaneous coronary interventionConfidence interval

Abstract

fetched live from OpenAlex

The REWIND trial showed that relative to placebo (PL), once weekly dulaglutide (DU) 1.5 mg reduced the incidence of a major adverse cardiovascular (CV) event (MACE; nonfatal myocardial infarction, nonfatal stroke, or CV death) in patients with T2D with and without established CV disease (hazard ratio (HR) 0.88, 95% CI [0.79, 0.99]; p=0.026). DU also significantly reduced A1C, body weight (BW), and systolic blood pressure (SBP) (Table). In this post-hoc assessment, a mediation analysis was used to estimate the degree to which the effect of DU on these risk factors could statistically account for its effect on MACE. Data were analyzed from 9901 patients who had 1257 first MACE events over 5.4 median yrs of observation. Those risk factors for which the updated mean on follow-up was significantly related to MACE were added to a separate Cox model that included DU allocation, the baseline [BL] value of the measurement and the updated mean of the variable as time dependent covariates. Only A1C satisfied this condition (Table), suggesting that BW and SBP did not mediate the effect of DU on MACE in this study population. The effect size of DU on the MACE outcome was attenuated by 36.1% after accounting for its effect on A1C (Table). In conclusion, the results suggest most of the CV benefit of DU on MACE is not attributable to the A1C, BW, or SBP-lowering effects of DU. Disclosure H.M. Colhoun: Advisory Panel; Self; AstraZeneca, Eli Lilly and Company, Novartis Pharmaceuticals Corporation, Novo Nordisk Inc., Regeneron Pharmaceuticals, Sanofi-Aventis. Research Support; Self; AstraZeneca, Eli Lilly and Company, Novo Nordisk Inc., Novo Nordisk Inc., Pfizer Inc., Regeneron Pharmaceuticals, Sanofi-Aventis. Speaker’s Bureau; Self; Eli Lilly and Company, Regeneron Pharmaceuticals, Sanofi. Stock/Shareholder; Self; Bayer AG, Roche Pharma. Other Relationship; Self; Eli Lilly and Company, Sanofi. C. Hasenour: Employee; Self; Eli Lilly and Company. M.C. Riddle: Consultant; Self; ADOCIA, Dance Biopharm Holdings, Inc., GlaxoSmithKline plc., Sanofi US, Theracos, Inc. Research Support; Self; AstraZeneca, Eli Lilly and Company, Novo Nordisk Inc. K. Branch: Consultant; Self; Bayer AG. Research Support; Self; Bayer AG, Eli Lilly and Company. M. Konig: Employee; Self; Eli Lilly and Company. C. Atisso: Employee; Self; Eli Lilly and Company. M. Lakshmanan: Employee; Self; Eli Lilly and Company. Stock/Shareholder; Self; Eli Lilly and Company. Stock/Shareholder; Spouse/Partner; Eli Lilly and Company. R. Mody: Employee; Self; Eli Lilly and Company. H.C. Gerstein: Advisory Panel; Self; Abbott, AstraZeneca, Boehringer Ingelheim (Canada) Ltd., Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk Inc., Sanofi. Consultant; Self; Kowa Pharmaceuticals America, Inc. Research Support; Self; AstraZeneca, Boehringer Ingelheim (Canada) Ltd., Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk Inc., Sanofi. Other Relationship; Self; Boehringer Ingelheim (Canada) Ltd., Eli Lilly and Company, Sanofi.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.202
Teacher spread0.180 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

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